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Remote monitoring system enabling cloud technology upon smart phones and inertial sensors for human kinematics

Karunarathne,MS, Jones,SA, Ekanayake,SW and Pathirana,PN 2014, Remote monitoring system enabling cloud technology upon smart phones and inertial sensors for human kinematics, in Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014, Institute of Electrical and Electronics Engineers Inc.,, pp. 137-142, doi: 10.1109/BDCloud.2014.62.

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Title Remote monitoring system enabling cloud technology upon smart phones and inertial sensors for human kinematics
Author(s) Karunarathne,MS
Jones,SA
Ekanayake,SW
Pathirana,PNORCID iD for Pathirana,PN orcid.org/0000-0001-8014-7798
Conference name BDCloud 2014 : Big Data and Cloud Computing
Conference location Sydney, Australia
Conference dates 3-5 Dec. 2014
Title of proceedings Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014
Publication date 2014
Start page 137
End page 142
Publisher Institute of Electrical and Electronics Engineers Inc.
Keyword(s) Cloud Computing
Human Activity Monitoring
Inertial Sensors
Mobile Applications
Physiotherapy
Sport
Summary Stroke is a common neurological condition which is becoming increasingly common as the population ages. This entails healthcare monitoring systems suitable for home use, with remote access for medical professionals and emergency responders. The mobile phone is becoming the easy access tool for self-evaluation of health, but it is hindered by inherent problems including computational power and storage capacity. This research proposes a novel cloud based architecture of a biomedical system for a wearable motion kinematic analysis system which mitigates the above mentioned deficiencies of mobile devices. The system contains three subsystems: 1. Bio Kin WMS for measuring the acceleration and rotation of movement 2. Bio Kin Mobi for Mobile phone based data gathering and visualization 3. Bio Kin Cloud for data intensive computations and storage. The system is implemented as a web system and an android based mobile application. The web system communicates with the mobile application using an encrypted data structure containing sensor data and identifiable headings. The raw data, according to identifiable headings, is stored in the Amazon Relational Database Service which is automatically backed up daily. The system was deployed and tested in Amazon Web Services.
ISBN 9781479967193
Language eng
DOI 10.1109/BDCloud.2014.62
Field of Research 080505 Web Technologies (excl Web Search)
080502 Mobile Technologies
090609 Signal Processing
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30071943

Document type: Conference Paper
Collections: School of Engineering
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